Beyond the Text: Digital Pedagogy, AI, and the Ethics of Technology

 Literature in the Digital Age: Hypertext, AI, and New Ways of Learning

This blog is a reflection on the learning and insights I gained through the FDP presentations, video lecture, and digital activities introduced as part of our learning experience under Dr. Dilip Barad Sir. The FDP on “A Pedagogical Shift from Text to Hypertext: Language & Literature to the Digital Natives” helped me understand how digital technology is transforming the ways in which language and literature are taught, studied, and interpreted. Along with exploring hypertext, digital pedagogy, Generative Literature, Digital Humanities, and digital assessment, I also engaged with the MIT Moral Machine activity, which encouraged me to think about the ethical questions involved in Artificial Intelligence and autonomous decision-making. These activities helped me move beyond simply reading theoretical concepts and allowed me to experience how digital tools can encourage critical thinking, reflection, and active learning. In this blog, I have brought together my learning from these activities and reflected on how they have influenced my understanding as an English literature student in the digital age.

 Introduction

As autonomous vehicles (AVs) move closer to mass deployment, the boundary between engineering and moral philosophy is rapidly dissolving. Self-driving cars must be programmed to react in unavoidable accident scenarios where every possible outcome results in harm.

To explore these dilemmas firsthand, I completed the MIT Moral Machine experiment an interactive platform that presents users with 13 moral dilemmas involving autonomous driving decisions. This reflection analyzes my specific results, compares my moral choices against global user averages, and evaluates the ethical implications of programming decision-making logic into artificial intelligence.

2. Analysis of My Results (Personal Data vs. Global Average)

The simulation evaluated my choices across several core ethical dimensions. Below is the breakdown based on my results summary:

Key Highlights

• Most Saved Character: Business Executive / Professional.

• Most Killed Character: Elderly Male.

pdf of result :click here

Detailed Breakdown

• Saving More Lives (Utilitarian Focus): My choices placed a heavy weight on minimizing the total loss of life, scoring much higher on "Matters a lot" than the global average. When forced to choose between one person or multiple individuals, I consistently saved the larger group.

• Protecting Passengers vs. Pedestrians: I strongly prioritized saving pedestrians over vehicle occupants, rating passenger protection as "Does Not Matter" in critical scenarios. My reasoning was that pedestrians are vulnerable road users who did not opt into taking a risk by stepping inside the vehicle.

• Species & Demographic Preferences:

  • Species: I strongly prioritized saving human lives over animals/pets, aligning with the global standard.

  • Age: Unlike the global average ("Others"), which leans toward saving younger individuals, my results leaned slightly toward protecting older individuals.

  • Social Value: My results showed a distinct tilt toward sparing characters with higher perceived social status (e.g., executives/professionals) over lower-status characters.

3. Ethical Frameworks & Critical Reflection

My decisions during the experiment revealed a mix of philosophical frameworks, along with implicit biases exposed by the forced constraints of the test:

Utilitarianism vs. Deontology

• Utilitarianism (Consequentialism): My strong preference for saving the maximum number of lives reflects a classic utilitarian approach—seeking the greatest good (or least harm) for the greatest number of people.

• Deontology (Duty & Rules): My willingness to sacrifice vehicle passengers to protect pedestrians reflects a duty-based framework where the system holds a fundamental obligation to protect innocent bystanders who have no control over the vehicle's trajectory.

Uncovering Unconscious Biases

The most challenging part of this exercise was seeing the demographic results. In an abstract discussion, I would argue that every human life holds equal worth. However, under the forced binary choices of the simulation, my decisions resulted in higher survival rates for individuals with higher social status. This highlights how split-second algorithmic choices can unintentionally codify systemic biases into automated software.

4. Key Learning Outcomes for AI Engineering

1. Moral Consensus is Difficult to Standardize: There is no universal "correct" formula for solving ethical dilemmas. What seems logical to a utilitarian engineer (e.g., swerving to hit 1 person instead of 3) might violate legal or duty-based ethics.

2. The Danger of Codifying Bias: If AI algorithms are trained on crowd-sourced data or reflecting human choice patterns, they risk inheriting human biases regarding age, gender, or social class.

3. Policy Over Pure Code: Engineers should not be the sole decision-makers regarding moral parameters in AI. Establishing ethical guidelines for autonomous systems requires input from ethicists, policymakers, legal scholars, and the public.

From Text to Hypertext: My Learning Journey in Digital Pedagogy

The FDP on “A Pedagogical Shift from Text to Hypertext: Language & Literature to the Digital Natives”, presented by Dr. Dilip Barad, helped me look at teaching and learning from a completely different perspective. Before studying this presentation, I mostly understood literature through books, classroom lectures, discussions, and traditional methods of interpretation. The FDP made me realize that in the digital age, literature can be explored through websites, images, videos, hyperlinks, digital archives, online tools, and even artificial intelligence.

For me, the most important idea was that the shift from text to hypertext is not simply a technological change. It is a change in the way teachers teach and students learn. It encourages students to explore, connect different sources, question fixed meanings, and participate actively in the learning process.

Part 1: Understanding the Shift from Text to Hypertext

If the presentation does not display above, open it directly: Open presentation in a new tab.

The first part of the presentation introduced the basic idea of digital pedagogy. The opening slides helped me understand why traditional teaching methods need to respond to the changing habits of today's students. Digital-native students are already familiar with websites, videos, social media, search engines, and interactive content. Therefore, simply transferring classroom notes to an online platform does not automatically make education digital.

One of the ideas that particularly interested me was hypertext. A traditional printed text generally follows a linear structure: we begin at one point and continue through the pages in a fixed order. Hypertext works differently. It allows us to move between texts, images, videos, websites, references, and other sources through links. While exploring one idea, we can immediately move towards another related idea.

This made me understand why hypertext is useful for literature. A poem, for example, can be connected to an image, a historical event, a painting, a geographical location, a video, or another literary text. In this way, reading becomes an active process of exploration.

This made me understand why hypertext is useful for literature. A poem, for example, can be connected to an image, a historical event, a painting, a geographical location, a video, or another literary text. In this way, reading becomes an active process of exploration.

From Teacher-Centred to Student-Centred Learning

Another important concept was decentering. In traditional classrooms, the teacher and the prescribed text often occupy the centre of the learning process. The teacher explains the meaning and students generally receive that explanation. Digital learning can change this relationship.

With hypertext, students can explore several sources and arrive at different interpretations. This does not mean that the teacher becomes unnecessary. Instead, the teacher becomes a facilitator or guide who helps students find reliable sources, ask useful questions, and develop their own interpretations.

I found this change particularly meaningful because literature itself does not always have one fixed interpretation. Digital resources can give students opportunities to approach a text from historical, cultural, visual, theoretical, and interdisciplinary perspectives.

Digital Classroom and Teaching Models

The presentation also introduced teaching models such as Flipped Classroom, Blended Learning, and Mixed Mode Teaching. I understood that these approaches give students greater responsibility for their own learning.

In a flipped classroom, students can engage with lectures or learning materials before coming to class. Classroom time can then be used for discussion, interpretation, activities, and problem-solving. Blended learning combines face-to-face teaching with digital resources, while mixed-mode teaching provides flexibility between online and offline learning.

The presentation also introduced digital platforms such as Learning Management Systems, Content Management Systems, and digital portfolios. These tools can help teachers organize materials, communicate with students, provide feedback, and document learning.

Learning through Digital Tools

The presentation then moved from theory to practical examples. Tools such as Lightboard and OBS Studio showed me how technology can make teaching more visual and interactive.

A Lightboard allows a teacher to write or draw while continuing to face the camera. When combined with OBS, different visual elements such as images, diagrams, animations, or videos can be included in a lesson. I found this especially useful for subjects like literature and literary theory, where concepts can sometimes feel abstract.

For example, poetry can be taught through a combination of text, sound, images, and explanation. Similarly, difficult theoretical concepts such as deconstruction can be represented through diagrams and visual explanations rather than relying only on lengthy verbal explanations.

The presentation also introduced the Watch → Think → Discuss approach through TED-Ed. This showed me that technology alone cannot make education effective. There must also be a thoughtful teaching strategy that encourages students to observe, reflect, discuss, and respond.

My Learning from Part 1

The first part helped me understand a clear progression:

Traditional text → Hypertext → Interactive learning → Student participation → Teacher as facilitator

I learned that digital pedagogy is not about replacing books or teachers with technology. Instead, it is about expanding the possibilities of learning.

 

Part 2: Hypertextual Solutions for Language and Literature

If the presentation does not display above, open it directly: Open presentation Part II in new tab.

The second part of the presentation focused more directly on the teaching of language and literature. It showed how digital tools can respond to some of the difficulties students face in understanding spoken language and literary texts.

Digital Tools for Language Learning

Learning a language is not limited to vocabulary and grammar. Pronunciation, stress, intonation, speed, and modulation are equally important. In online learning, students may sometimes miss words because of pronunciation, network problems, accent differences, or the speed of speech.

The presentation introduced tools such as Chrome Live Caption, transcription tools for Google Meet, and Google Docs Voice Typing. These tools can convert spoken language into written form and therefore make oral communication easier to follow.

I realized that such tools can be useful not only for students who have difficulty understanding spoken English but also for taking notes, preparing assignments, reviewing lectures, and improving listening skills.

Making Difficult Literary Images Understandable

One of the most interesting examples in the presentation involved a poetic description of hawthorns and the image of a blue pitcher. At first, a student who has never seen a hawthorn plant may find the image difficult to imagine.

Here hypertext becomes very useful. Instead of only explaining the meaning verbally, a teacher can show photographs of hawthorn flowers. The student can then connect the words in the poem with an actual visual object.

Similarly, searching for the cultural reference connected with the “blue pitcher” can help students understand the poet's imaginative comparison.

This example taught me an important lesson: sometimes students do not fail to understand literature because the language is difficult; they may simply lack the cultural or visual background required to understand the image.

Digital resources can help bridge this gap.

Google Arts & Culture and Literary Learning

Another example that attracted my attention was the use of Google Arts & Culture for teaching the myth of Icarus and Daedalus.

Instead of simply asking students to read the myth, a teacher can encourage them to explore paintings, exhibitions, historical material, and literary responses connected with Icarus. Students can search for representations such as The Fall of Icarus and compare different artistic interpretations.

This transforms the lesson into an exploratory activity. Students are no longer receiving one explanation from the teacher; they are searching, comparing, connecting, and interpreting.

It also helped me understand the idea of decentring the centre. When students encounter several versions and representations of a story, they begin to understand that meaning does not necessarily come from one fixed or authoritative interpretation.

My Learning from Part 2

The second part taught me that hypertext can act as a bridge between the learner and the literary world.

• A difficult word can be connected to a definition.
• A difficult image can be connected to a photograph.
• A cultural reference can be connected to an archive.
• A myth can be connected to paintings and historical material.
• A literary text can be connected to other texts and forms of art.

In this way, literature becomes more accessible without reducing its complexity.

Part 3: Generative Literature, Digital Humanities and Digital Assessment

The third part of the presentation introduced some of the most contemporary aspects of digital literary studies. It moved beyond using technology for teaching and showed how technology itself is changing the nature of literature and literary research.

Generative Literature

One concept that was new and interesting for me was generative literature. According to the presentation, generative literature involves texts produced through computers, dictionaries, rules, algorithms, or other programmed systems.

This made me think about a basic question: If a machine produces a poem, who is the author?

Traditional literature is usually associated with a human writer who creates a work intentionally. Generative literature complicates this idea because the final text may be produced through a combination of human programming and computational processes.

Poem generators can create forms such as haiku, sonnets, or songs by following particular rules. This does not simply give us a new method of writing; it also creates new questions about creativity, authorship, originality, and the role of the reader.

Digital Humanities and New Ways of Reading

The presentation also connected digital pedagogy with Digital Humanities. This was particularly relevant to me as a student of English literature because it showed me that computers can be used not only for writing and communication but also for literary research.

The ideas of microanalysis and macroanalysis, associated with Matthew Jockers, helped me understand the difference between studying a small part of a text closely and studying a large number of texts using computational methods.

Traditional close reading allows us to examine a particular word, image, character, or passage in detail. Computational methods can help researchers examine thousands of texts and identify larger patterns.

The idea of culturomics, associated with large-scale analysis of cultural data, further demonstrated how digital methods can reveal changes in language and culture over long periods.

CLiC and Corpus-Based Literary Study

The presentation also introduced CLiC, a corpus-based digital tool that can be used for studying literary texts, particularly nineteenth-century literature.

What I found interesting about CLiC is that it allows a reader to investigate patterns that may not be immediately visible during ordinary reading. By looking at words in context and comparing their uses, students can develop evidence-based interpretations.

This connects digital tools with traditional literary criticism. The computer does not replace interpretation; rather, it can provide additional evidence that supports or challenges our interpretation.

Digital Portfolio as Assessment

Another idea that I found useful was the digital portfolio.

In a traditional system, students complete an assignment, submit it, receive marks, and then move on to the next task. A digital portfolio changes this process. Students can collect their blogs, presentations, projects, reflections, videos, and other work in one digital space.

For me, this changes the meaning of assessment. Instead of assessment being only about marks, it can become a record of the student's intellectual development.

A digital portfolio can show not only what I have learned, but also how my understanding has changed over time.

Video Lecture: From Text to Hypertext in Digital Pedagogy

The video lecture further developed the ideas introduced in the presentation. It explained why the transition from text to hypertext has become increasingly important in contemporary education.

One of the strongest points for me was the idea that teachers should develop their own digital presence. Many teachers use platforms such as YouTube, Google Classroom, or other institutional systems, but having a personal blog or website can give educators greater independence in organizing and sharing their academic resources.

The lecture also discussed some challenges of online teaching. Online education can reduce face-to-face interaction and make it difficult to read students' non-verbal responses. Students may also lose concentration or face technical and network-related difficulties.

However, the lecture showed that digital tools can be used creatively to address some of these problems. Glass boards, collaborative Google Docs, captions, transcription tools, and recorded lectures can make online learning more interactive and accessible.

The lecture also emphasized blended and flipped learning. These approaches combine live interaction with digital and recorded materials, giving students opportunities to learn both inside and outside the classroom.

Another important point was privacy and responsible digital communication. Digital education should not simply focus on using more technology. Teachers and students must also think about privacy, security, responsible sharing, and digital citizenship.

My Overall Learning Outcome 

After going through all three parts of the presentation and the video lecture, I now understand that the movement from text to hypertext represents a much larger pedagogical transformation.

Earlier, I thought digital learning mainly meant studying through a computer, watching online lectures, or accessing PDFs. Now I understand that digital pedagogy involves a much broader process of connecting, exploring, creating, collaborating, and interpreting.

The teacher's role is changing from being the only source of information to becoming a facilitator who guides students through different sources.

The student's role is also changing. Students are not expected merely to receive information. They are encouraged to search, question, compare, create, and construct meaning.

For literature students, this shift is particularly valuable. A poem can lead us to an image; an image can lead us to a painting; the painting can lead us to history; history can lead us to another literary text. In this way, one text can open into a whole network of knowledge.

I also learned that technology should not be used simply because it is new. The tool should serve the learning objective. A digital tool becomes meaningful only when it helps students understand, question, discuss, or create something more effectively.

Most importantly, this FDP changed the way I think about my own learning as an English literature student. Literature is no longer limited to the printed page. At the same time, technology does not make traditional literary study irrelevant. Instead, both can work together.

The movement from text to hypertext therefore does not mean leaving the text behind. It means opening the text to new connections, perspectives, technologies, and possibilities.

Conclusion

The FDP and video lecture gave me a new understanding of the relationship between literature, technology, and education. I learned about hypertext, digital pedagogy, flipped and blended learning, digital tools, generative literature, Digital Humanities, corpus analysis, and digital portfolios.

More importantly, I learned that the digital classroom should not simply reproduce the traditional classroom on a screen. It should create opportunities for students to become active participants in the learning process.

For me, the central lesson of this entire experience can be expressed simply:

From text to hypertext is not just a movement from one medium to another; it is a movement from receiving knowledge to actively exploring and creating it.

This has encouraged me to think of digital technology not as a replacement for literature or traditional learning, but as a new space through which literature can be explored more creatively, critically, and interactively.

REFERENCE : 

Barad, Dilip. “Pedagogical Shift from Text to Hypertext: Language & Literature to the Digital Natives.” Dilip Barad | Teacher Blog, 18 Sept. 2021, https://blog.dilipbarad.com/2021/09/pedagogical-shift-from-text-to.html.

From Human Creativity to Machine Intelligence: Exploring Literature in the Digital Age

Reading Beyond the Page: Exploring Literature Through AI, CLiC and Voyant Tools

Digital Humanities has opened new possibilities for the study of literature by bringing together traditional literary interpretation and digital technologies. As part of the activities assigned by Dr. And professor Dilip Barad sir , I explored the relationship between literature, artificial intelligence, and digital tools through a series of practical activities involving AI, CLiC, and Voyant Tools. These activities encouraged me to look at literature not only through close reading but also through computational methods such as frequency analysis, concordance, visualisation, and distant reading. The discussion of Oscar Schwartz’s question, “Can a Computer Write Poetry?”, made me think critically about creativity, authorship, meaning, and the difference between producing language and understanding it. Similarly, using CLiC and Voyant Tools helped me discover patterns in literary texts that are not always immediately visible through traditional reading. Overall, these activities gave me a broader understanding of how technology can complement literary studies and helped me see Digital Humanities as a bridge between humanistic interpretation and computational analysis.

Oscar Schwartz asks a very interesting question: Can a computer actually write poetry, or can it only produce something that looks like poetry?

He explains that computers can be programmed to generate poems by learning patterns from existing poetry. The result can sometimes look surprisingly human. But the important question is not simply “Can a computer produce a poem?” It is:

Does a computer understand what it is creating?

The talk explores the difference between producing language and experiencing meaning.

Main ideas

1. Computers can generate poetry

A computer can analyse large amounts of poetry and learn patterns such as vocabulary, sentence structures, rhythm and poetic forms. It can then combine these patterns to create new poems.

2. A poem can look human even when a computer created it

Schwartz demonstrates that computer-generated poetry can sometimes be difficult for people to distinguish from poetry written by humans. This challenges our assumption that creativity automatically belongs only to humans.

3. The Turing Test is important

The talk connects this issue to Alan Turing's idea of testing machine intelligence. If a machine can communicate in a way that humans cannot distinguish from another human, we may begin to question whether the machine is intelligent.

But Schwartz asks whether this test is enough for creative works such as poetry.

4. Producing language 

This is probably the most important idea for your class.

A computer may arrange words correctly without having personal experiences, emotions, memories, or intentions behind those words.

For example, a computer can produce a poem about sadness, but that doesn't necessarily mean the computer has experienced sadness.

5. Poetry is connected to human experience

Poetry isn't only about putting beautiful words together. Human poets write from experiences, emotions, memories, cultural backgrounds and particular intentions.

Therefore, Schwartz makes us question whether a machine-generated poem has the same kind of meaning as a poem created by a human.

The central question

The video is ultimately asking:

If a computer produces a poem that makes us feel something, does it matter whether a human or a machine wrote it?

There are two possible ways to look at it:

• Yes, it matters: Human creativity involves consciousness, experience, emotion and intention.
• Maybe it doesn't: If the poem communicates meaning and creates an emotional response in the reader, perhaps the origin of the poem is less important.

Why this video is important for Digital Humanities / AI

This video is useful for understanding the relationship between technology and literature. It shows that AI doesn't simply affect science or technology—it also challenges traditional ideas about authorship, creativity, originality and literary value.

A key takeaway is:

AI can imitate the patterns of human creativity, but the video makes us question whether imitation is the same thing as genuine creativity.

This is also why the video is often used in discussions of AI and literature/poetry.

In very simple words

Computer: “I can create a poem because I have learned patterns from thousands of poems.”

Human: “But do you understand what the poem means or why you are writing it?”

Schwartz: “That is exactly the question we need to think about.”

My Experience of the Human or Computer Test 

As part of the activity, I took a test to identify whether the poems were written by a human or a computer. I read each poem carefully and made my choice based on the language, imagery, structure, and connection between ideas.

At first, I thought I could easily distinguish human writing from computer-generated writing. However, the test was more challenging than I expected. Some poems had emotional and natural-sounding language, while others had unusual combinations of words and ideas.

For this particular poem, I chose “A Machine,” but my answer was wrong. The result revealed that the poem was actually written by Thomas Kinder, a human. This surprised me because the poem has a very structured and polished style, and I initially thought it might have been generated by AI.

The test showed me that AI can sound human, and human writing can sometimes sound like AI. My score was 4 out of 6, which made me realise that it is not always possible to identify the author simply by reading the poem.

Overall, this experience was useful and interesting. It encouraged me to read poetry more carefully and critically. I learned that I should not judge a poem as AI-generated only because its language seems unusual or highly structured. The activity helped me understand the difficulty of distinguishing human creativity from computer-generated writing. 

My Experience with CLiC: Distant Reading

My Experience of Using CLiC to Study “Chin”

Using CLiC to study the word “chin” was an interesting and eye-opening experience for me. I found that the word appeared much more frequently in Dickens’s novels than in Jane Austen’s works. By comparing the frequency of “chin” across different corpora, I understood how corpus tools can help us notice patterns that we might not notice through ordinary reading.

Looking at the concordance lines was especially useful because it showed me how Dickens used physical descriptions to create and develop his characters. The description of a character’s chin could suggest their appearance, personality, social class, or even their state of mind. I also learned that a simple body part can have a deeper role in characterisation.

This activity helped me understand that language choices are closely connected to literary meaning. Frequency counts gave me evidence, while the concordance examples helped me interpret that evidence. Overall, the activity gave me a new perspective on how body language and physical description contribute to characterisation in fiction.

Voyant Tools Analysis of The Importance of Being Earnest

I used Voyant Tools to analyse Oscar Wilde’s The Importance of Being Earnest. The word cloud shows that Jack, Algernon, Gwendolen, Lady, and Cecily are among the most frequent words, highlighting the importance of these characters. The corpus contains 9,945 words and 1,669 unique word forms. The Trends graph shows how the prominence of characters changes across different sections of the play, while the Contexts tool helps examine how particular words are used in dialogue. Overall, Voyant shows that Wilde’s play is strongly character- and dialogue-driven, reflecting themes of identity, deception, relationships, and social performance.

Bubblelines Analysis of The Importance of Being Earnest

The Bubblelines visualization shows the frequency and connections of words and characters in Oscar Wilde’s The Importance of Being Earnest. Gwendolen, Algernon, Lane, and Jack appear prominently, indicating their importance in the text. The larger circles suggest words that occur more frequently or have stronger connections, while the smaller circles represent less frequent terms. The visualization also highlights recurring words such as “earnest,” “importance,” “married,” “love,” “lady,” and “young,” which connect to the play’s major concerns with marriage, identity, social class, and relationships. Overall, the Bubblelines visualization helps us see the structure and recurring vocabulary of the play through a digital approach.

Trends Analysis of The Importance of Being Earnest

The Trends visualization shows how the frequency of important characters and words changes across the text. Jack, Algernon, Gwendolen, Cecily, and Lady appear repeatedly throughout different sections, showing their continuing importance to the play. The larger bubbles indicate moments where these words occur more frequently, while the changing patterns show how the focus shifts between characters as the plot develops. This visualization demonstrates that Wilde’s play is strongly character- and dialogue-centred, with recurring attention to identity, relationships, marriage, and social expectations.

Trends Analysis of The Importance of Being Earnest

The Trends graph shows the distribution of Lady, Jack, Gwendolen, Algernon, and “844” across the ten sections of the text. Algernon and Jack appear strongly in several sections, while Gwendolen becomes especially prominent around section 5–6 and Lady is most noticeable around section 6. The graph shows that the focus shifts between characters as the play progresses. Overall, it demonstrates how Wilde’s plot develops through character interactions, relationships, and changing dramatic focus, especially around themes of identity, love, marriage, and social expectations.

My Collective Learning Outcomes

After completing the activities with AI, CLiC, and Voyant Tools, I discussed my learning outcomes with my group members. We came to a few important collective realizations:

• A Complementary Approach: We understood that digital tools do not replace traditional literary criticism. Instead, tools like CLiC and Voyant provide quantitative evidence that can support our interpretations and close reading.

• Bridging the Tech Gap: Initially, some of us found the digital tools and technical interfaces confusing. We realized that as literature students, we need to become more comfortable with technology because digital methods are becoming an important part of modern literary research.

• Developing New Questions: The activities taught us to look beyond simply asking “What does this text mean?” We also learned to ask “How often does a word appear?” “Where does it appear?” and “In what context is it used?”

• Critical Understanding of AI: The Human or Computer Test made us realize that human and AI-generated writing can sometimes be difficult to distinguish, encouraging us to think critically about creativity, authorship, and meaning.

• Connecting Technology and Literature: Overall, the session helped us understand how Digital Humanities connects computational tools with literary interpretation.

This was challenging at first, but it was also interesting and rewarding. It encouraged me to explore digital tools more confidently and apply them to my future literary studies and research.

REFERENCE :

Schwartz, Oscar. “Can a Computer Write Poetry?” TED, TEDxYouth@Sydney, 2015. TED Talk

Barad, Dilip. "What if Machines Write Poems." Dilip Barad | Teacher Blog, 21 Mar. 2017, blog.dilipbarad.com/2017/03/what-if-machines-write-poems.html.

Sinclair, Stéfan, and Geoffrey Rockwell. Voyant Tools. 2016, beta.voyant-tools.org. Accessed 11 Aug. 2026.